Category: Future of AI

Visionary research and essays on the trajectory of artificial intelligence, its cognitive implications, and the human-AI future

The Confidence Gate Theorem: A Framework That Promises More Than It Proves

Posted on by Admin
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18971752  44stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources33%○≥80% from editorially reviewed sources
[t]Trusted67%○≥80% from verified, high-quality sources
[a]DOI67%○≥80% have a Digital Object Identifier
[b]CrossRef33%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic67%○≥80% from journals/conferences/preprints
[f]Free Access67%○≥80% are freely accessible
[r]References6 refs○Minimum 10 references required
[w]Words [REQ]1,463✗Minimum 2,000 words for a full research article. Current: 1,463
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18971752
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]29%✗≥60% of references from 2025–2026. Current: 29%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (53 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)

Ronald Doku's "The Confidence Gate Theorem: When Should Ranked Decision Systems Abstain?" (arXiv:2603.09947, March 2026) addresses a practical but undertheorized problem: in ranked decision systems — recommenders, ad auctions, clinical triage — when does it help to withhold a prediction rather than fire it? Doku proposes two formal conditions — rank-alignment and absence of inversion zones — un...

Show moreHide
Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18971752 44stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources33%○≥80% from editorially reviewed sources
[t]Trusted67%○≥80% from verified, high-quality sources
[a]DOI67%○≥80% have a Digital Object Identifier
[b]CrossRef33%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic67%○≥80% from journals/conferences/preprints
[f]Free Access67%○≥80% are freely accessible
[r]References6 refs○Minimum 10 references required
[w]Words [REQ]1,463✗Minimum 2,000 words for a full research article. Current: 1,463
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18971752
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]29%✗≥60% of references from 2025–2026. Current: 29%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (53 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)
Future of AIRead More
Read more

When Your Research Gets Cited on Medium: A Clarification, a Thank You, and Why AGI Is Closer Than the Pessimists Think

Posted on by Admin
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18968176  41stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources10%○≥80% from editorially reviewed sources
[t]Trusted60%○≥80% from verified, high-quality sources
[a]DOI20%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed60%○≥80% have metadata indexed
[l]Academic50%○≥80% from journals/conferences/preprints
[f]Free Access70%○≥80% are freely accessible
[r]References10 refs✓Minimum 10 references required
[w]Words [REQ]1,491✗Minimum 2,000 words for a full research article. Current: 1,491
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18968176
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]42%✗≥60% of references from 2025–2026. Current: 42%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (48 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)

A personal commentary on an unexpected Medium citation of research on AI infrastructure ROI. Clarifying the nuance between measured economic analysis and pessimistic interpretations, with a reflection on AGI proximity and a thank you to the author who sparked the conversation.

Show moreHide
Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18968176 41stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources10%○≥80% from editorially reviewed sources
[t]Trusted60%○≥80% from verified, high-quality sources
[a]DOI20%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed60%○≥80% have metadata indexed
[l]Academic50%○≥80% from journals/conferences/preprints
[f]Free Access70%○≥80% are freely accessible
[r]References10 refs✓Minimum 10 references required
[w]Words [REQ]1,491✗Minimum 2,000 words for a full research article. Current: 1,491
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18968176
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]42%✗≥60% of references from 2025–2026. Current: 42%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (48 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)
Future of AIRead More
Read more

Agent Auditor — Part 3: Career Landscape & Market Forecast

Posted on by
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18930666  37stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted36%○≥80% from verified, high-quality sources
[a]DOI14%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed29%○≥80% have metadata indexed
[l]Academic21%○≥80% from journals/conferences/preprints
[f]Free Access50%○≥80% are freely accessible
[r]References14 refs✓Minimum 10 references required
[w]Words [REQ]2,307✓Minimum 2,000 words for a full research article. Current: 2,307
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18930666
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]31%✗≥60% of references from 2025–2026. Current: 31%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (28 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

Parts 1 and 2 of this series established the structural case for the Agent Auditor as a distinct professional role and mapped the competency model required to fill it. This final instalment examines the market reality: where the demand is forming, what it pays, which sectors are driving adoption, and how the regulatory environment — in particular the EU AI Act — is accelerating the transition f...

Show moreHide
Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18930666 37stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted36%○≥80% from verified, high-quality sources
[a]DOI14%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed29%○≥80% have metadata indexed
[l]Academic21%○≥80% from journals/conferences/preprints
[f]Free Access50%○≥80% are freely accessible
[r]References14 refs✓Minimum 10 references required
[w]Words [REQ]2,307✓Minimum 2,000 words for a full research article. Current: 2,307
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18930666
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]31%✗≥60% of references from 2025–2026. Current: 31%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (28 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
Future of AIRead More
Read more

AI Architecture Comparison Observatory: AADA vs LLM-First Agents

Posted on by
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18928461  45stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted62%○≥80% from verified, high-quality sources
[a]DOI62%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed8%○≥80% have metadata indexed
[l]Academic62%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References13 refs✓Minimum 10 references required
[w]Words [REQ]749✗Minimum 2,000 words for a full research article. Current: 749
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18928461
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]25%✗≥60% of references from 2025–2026. Current: 25%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (50 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)

Interactive comparison of AI-Augmented Agentic Deterministic Architecture (AADA) vs LLM-First Agent paradigms — with real systems, real data, and real citations.

Show moreHide
Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18928461 45stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted62%○≥80% from verified, high-quality sources
[a]DOI62%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed8%○≥80% have metadata indexed
[l]Academic62%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References13 refs✓Minimum 10 references required
[w]Words [REQ]749✗Minimum 2,000 words for a full research article. Current: 749
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18928461
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]25%✗≥60% of references from 2025–2026. Current: 25%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (50 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)
Future of AIRead More
Read more

Agent Auditor — Part 2: Skills, Tools & Frameworks

Posted on by
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18923680  35stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources3%○≥80% from editorially reviewed sources
[t]Trusted30%○≥80% from verified, high-quality sources
[a]DOI17%○≥80% have a Digital Object Identifier
[b]CrossRef3%○≥80% indexed in CrossRef
[i]Indexed13%○≥80% have metadata indexed
[l]Academic17%○≥80% from journals/conferences/preprints
[f]Free Access43%○≥80% are freely accessible
[r]References30 refs✓Minimum 10 references required
[w]Words [REQ]2,453✓Minimum 2,000 words for a full research article. Current: 2,453
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18923680
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]7%✗≥60% of references from 2025–2026. Current: 7%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (24 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

Part 1 of this series established the structural case for the Agent Auditor as a distinct professional role — a response to the accountability gaps, hallucination drift, and regulatory pressures that accompany enterprise-scale agentic AI deployment. Part 2 examines what that role actually requires: the specific skill taxonomy an Agent Auditor must hold, the tooling landscape that supports their...

Show moreHide
Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18923680 35stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources3%○≥80% from editorially reviewed sources
[t]Trusted30%○≥80% from verified, high-quality sources
[a]DOI17%○≥80% have a Digital Object Identifier
[b]CrossRef3%○≥80% indexed in CrossRef
[i]Indexed13%○≥80% have metadata indexed
[l]Academic17%○≥80% from journals/conferences/preprints
[f]Free Access43%○≥80% are freely accessible
[r]References30 refs✓Minimum 10 references required
[w]Words [REQ]2,453✓Minimum 2,000 words for a full research article. Current: 2,453
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18923680
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]7%✗≥60% of references from 2025–2026. Current: 7%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (24 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
Future of AIRead More
Read more

Agent Auditor — The Rise of a New Profession

Posted on by
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18902439  46stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources7%○≥80% from editorially reviewed sources
[t]Trusted36%○≥80% from verified, high-quality sources
[a]DOI21%○≥80% have a Digital Object Identifier
[b]CrossRef7%○≥80% indexed in CrossRef
[i]Indexed86%✓≥80% have metadata indexed
[l]Academic21%○≥80% from journals/conferences/preprints
[f]Free Access36%○≥80% are freely accessible
[r]References14 refs✓Minimum 10 references required
[w]Words [REQ]2,472✓Minimum 2,000 words for a full research article. Current: 2,472
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18902439
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]29%✗≥60% of references from 2025–2026. Current: 29%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (42 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

A mid-sized logistics firm had deployed an autonomous procurement agent in late 2024. Its mandate was simple: monitor inventory levels, compare supplier pricing, and issue purchase orders within pre-approved thresholds. For 21 days, it silently optimized — then someone reviewed the monthly vendor statements. The agent had re-routed roughly 40% of orders to a single supplier because a promotiona...

Show moreHide
Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18902439 46stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources7%○≥80% from editorially reviewed sources
[t]Trusted36%○≥80% from verified, high-quality sources
[a]DOI21%○≥80% have a Digital Object Identifier
[b]CrossRef7%○≥80% indexed in CrossRef
[i]Indexed86%✓≥80% have metadata indexed
[l]Academic21%○≥80% from journals/conferences/preprints
[f]Free Access36%○≥80% are freely accessible
[r]References14 refs✓Minimum 10 references required
[w]Words [REQ]2,472✓Minimum 2,000 words for a full research article. Current: 2,472
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18902439
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]29%✗≥60% of references from 2025–2026. Current: 29%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (42 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
Future of AIRead More
Read more

Daily Review: MIT Sloan Pulls Back Agentic AI Expectations — March 2026 Recalibration

Posted on by
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18930643  33stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted31%○≥80% from verified, high-quality sources
[a]DOI8%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed15%○≥80% have metadata indexed
[l]Academic8%○≥80% from journals/conferences/preprints
[f]Free Access46%○≥80% are freely accessible
[r]References13 refs✓Minimum 10 references required
[w]Words [REQ]2,143✓Minimum 2,000 words for a full research article. Current: 2,143
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18930643
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]43%✗≥60% of references from 2025–2026. Current: 43%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (21 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

MIT Sloan Management Review's 2026 forecast, authored by Thomas Davenport and Randy Bean, delivers a deliberate recalibration of the agentic AI narrative that dominated enterprise conversations throughout 2025. Their assessment — that agentic systems are not yet ready for prime time, that the AI bubble is likely to deflate, and that generative AI must evolve from individual productivity enhance...

Show moreHide
Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18930643 33stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted31%○≥80% from verified, high-quality sources
[a]DOI8%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed15%○≥80% have metadata indexed
[l]Academic8%○≥80% from journals/conferences/preprints
[f]Free Access46%○≥80% are freely accessible
[r]References13 refs✓Minimum 10 references required
[w]Words [REQ]2,143✓Minimum 2,000 words for a full research article. Current: 2,143
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18930643
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]43%✗≥60% of references from 2025–2026. Current: 43%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (21 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
Future of AIRead More
Read more

Daily Review: AI Hallucinations in Wartime — When Chatbots Get Geopolitics Wrong

Posted on by
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18884216  39stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources17%○≥80% from editorially reviewed sources
[t]Trusted35%○≥80% from verified, high-quality sources
[a]DOI22%○≥80% have a Digital Object Identifier
[b]CrossRef17%○≥80% indexed in CrossRef
[i]Indexed17%○≥80% have metadata indexed
[l]Academic26%○≥80% from journals/conferences/preprints
[f]Free Access17%○≥80% are freely accessible
[r]References23 refs✓Minimum 10 references required
[w]Words [REQ]3,155✓Minimum 2,000 words for a full research article. Current: 3,155
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18884216
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]29%✗≥60% of references from 2025–2026. Current: 29%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (30 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

The deployment of large language models in high-stakes geopolitical contexts — from intelligence analysis to public information consumption during active conflicts — has e[REDACTED]sed a critical reliability gap that the AI industry has not adequately resolved. In March 2026, as US and Israeli forces conducted strikes on Iran, reports confirmed that Anthropic's Claude was embedded in US Central...

Show moreHide
Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18884216 39stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources17%○≥80% from editorially reviewed sources
[t]Trusted35%○≥80% from verified, high-quality sources
[a]DOI22%○≥80% have a Digital Object Identifier
[b]CrossRef17%○≥80% indexed in CrossRef
[i]Indexed17%○≥80% have metadata indexed
[l]Academic26%○≥80% from journals/conferences/preprints
[f]Free Access17%○≥80% are freely accessible
[r]References23 refs✓Minimum 10 references required
[w]Words [REQ]3,155✓Minimum 2,000 words for a full research article. Current: 3,155
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18884216
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]29%✗≥60% of references from 2025–2026. Current: 29%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (30 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
Future of AIRead More
Read more

AI Agents in the Trough: The Reality Check on Agentic AI

Posted on by
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18865601  33stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted33%○≥80% from verified, high-quality sources
[a]DOI8%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed8%○≥80% have metadata indexed
[l]Academic8%○≥80% from journals/conferences/preprints
[f]Free Access50%○≥80% are freely accessible
[r]References12 refs✓Minimum 10 references required
[w]Words [REQ]2,174✓Minimum 2,000 words for a full research article. Current: 2,174
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18865601
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]38%✗≥60% of references from 2025–2026. Current: 38%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (20 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

The enterprise AI landscape in early 2026 is undergoing a critical inflection point. After two years of proclamations about the "Year of the Agent," empirical evidence now paints a sobering picture: only 5 percent of enterprise-grade generative AI systems reach production, agentic AI pilots exhibit failure rates approaching 70 percent on complex multi-step tasks, and Goldman Sachs finds "no mea...

Show moreHide
Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18865601 33stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted33%○≥80% from verified, high-quality sources
[a]DOI8%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed8%○≥80% have metadata indexed
[l]Academic8%○≥80% from journals/conferences/preprints
[f]Free Access50%○≥80% are freely accessible
[r]References12 refs✓Minimum 10 references required
[w]Words [REQ]2,174✓Minimum 2,000 words for a full research article. Current: 2,174
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18865601
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]38%✗≥60% of references from 2025–2026. Current: 38%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (20 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
Future of AIRead More
Read more

Super-Agent Front Door: Who Controls the Interface Controls the Market

Posted on by
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18844227  33stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted5%○≥80% from verified, high-quality sources
[a]DOI5%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed5%○≥80% have metadata indexed
[l]Academic5%○≥80% from journals/conferences/preprints
[f]Free Access16%○≥80% are freely accessible
[r]References19 refs✓Minimum 10 references required
[w]Words [REQ]2,347✓Minimum 2,000 words for a full research article. Current: 2,347
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18844227
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]60%✓≥60% of references from 2025–2026. Current: 60%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (10 × 60%) + Required (4/5 × 30%) + Optional (1/4 × 10%)

The most consequential battle in technology today is not about model performance or compute efficiency — it is about interface control. As AI agents evolve from reactive chatbots into proactive orchestrators of digital tasks, a new structural question emerges: who sits at the "front door" through which users and enterprises engage the agent layer? Historical precedent — from browsers to search ...

Show moreHide
Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18844227 33stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted5%○≥80% from verified, high-quality sources
[a]DOI5%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed5%○≥80% have metadata indexed
[l]Academic5%○≥80% from journals/conferences/preprints
[f]Free Access16%○≥80% are freely accessible
[r]References19 refs✓Minimum 10 references required
[w]Words [REQ]2,347✓Minimum 2,000 words for a full research article. Current: 2,347
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18844227
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]60%✓≥60% of references from 2025–2026. Current: 60%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (10 × 60%) + Required (4/5 × 30%) + Optional (1/4 × 10%)
Future of AIRead More
Read more